@elonmusk Everyone is fear mongering on the issue this will cause. Where are the leaders offering solutions. Or is this just "hope you have enough cash saved up by 18 months time"
I automated my content engine and 2 hrs/day dropped to 10 min
[ what’s new in v2 ]:
- 9 platforms scraped while I sleep → 2,000+ topics/day
- a 5-signal scoring brain that filters down to the 10 that matter
- voice DNA writer.. same tone, different structure every time
- a self-learning loop that remembers every approve and decline
- profile DNA — knows exactly what goes viral on MY account
v1 was a brain with no body
v2 has eyes, a filter, and memory + fully automated
Here’s how to build it step-by-step ↓
[ The architecture]:
/content-engine
├── scrapers/ (9 platform scrapers)
├── extension/ (chrome ext for X, linkedin, reddit)
├── ai/
│ ├── https://t.co/JLmuw236QH (5-signal scoring brain)
│ ├── content_writer.py (voice DNA + structures)
│ ├── profile_analyzer.py (your positioning DNA)
│ └── sentiment_analyzer.py
├── publisher/ (export + time slot scheduling)
├── gui/dashboard.py (streamlit command center)
├── ingest_server.py (local server on localhost)
└── data/content_engine.db (everything stored locally)
let me walk you through each layer ↓
LAYER 1: Research engine
9 sources scanned 24/7 (X, reddit, YT, HN, github, trends + chrome ext for reddit and linkedin)
every post you scroll past gets tagged and stored locally
LAYER 2: Scoring brain
every topic scored on 5 signals:
- freshness (0.20)
- velocity (0.25)
- virality (0.25)
- relevance (0.20)
- uniqueness (0.10)
velocity 8+ → forced min score of 7. catches late bloomers that suddenly explode
2,000 topics → top 10 ranked
LAYER 3: Voice DNA writer
not one structure every time. system picks the format:
- short take
- tactical playbook
- QT contrast
- contrarian
- resource drop
- proof post
a voice guardian auto-rewrites anything that fails: lowercase ratio, no hashtags, no corporate words
LAYER 4: Dashboard Streamlit
dark theme. 5 tabs
review queue = tinder for content. swipe approve, swipe decline
LAYER 5: Publishing
no auto-posting. zero account risk
approve → pick a slot (8am / 12pm / 5pm) → exports a .txt → copy / paste / post
also auto-drafts a linkedin version of every approved tweet
LAYER 6: Self-learning loop
every click logged. weekly the system embeds your decline notes and re-tunes the scoring brain
month 1: you approve 30%
month 3: 70% pre-filtered
month 6: 10 min/day
LAYER 7: Profile DNA
analyzes your past tweets. tells you exactly which pillars, formats, and hooks perform best on YOUR account
the scoring brain uses it to prioritize what already works for you
daily run: open dashboard → 10 min reviewing → post 3x → close
total cost: ~$15/month
everything else: local, sqlite, no cloud, no subscription
unfortunately I couldn’t paste in long-form format initial description which was made before
but if this hits 2,000 likes I drop the full build guide with every prompt you need to ship it in claude code
reply "ENGINE" + RT and I'll DM you access to test it (follow me first so I can write)
save this so you don't lose it
7 mins into using Opus 4.7 and "You are right. I was sloppy."
Look, the models are getting but but please stop fear mongering for click bait.... we're not quite at the moment where you're going to come home and Claude will be fucking your wife.......
AI is making it much easier to create viral posts.
Soon, almost anyone will be able to make content that gets hundreds of thousands of likes.
Things that are hard to do usually feel more valuable. When going viral becomes easy for everyone, what will it mean for social media?
Then what will be the value in going viral?